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检索条件"任意字段=Scientific Conference on Mechatronics Engineering and Computer Science"

共 38171 条记录，以下是821-830 订阅

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A Novel Approach of Particle Swarm and ANT Colony Optimization for Task Scheduling in Cloud 14

A Novel Approach of Particle Swarm and ANT Colony Optimizati...

引用

14th International conference on Cloud Computing, Data science and engineering, Confluence 2024

作者： Kaliappan, Seeniappan Paranthaman, V. Kamal, M.D. Raj Sudhakar, A.V.V. Muthukannan, M. Kcg College of Technology Department of Mechatronics Engineering Karapakkam Tamil Nadu Chennai600097 India Adhi College of Engineering and Technology Department of Mechanical Engineering Tamilnadu Chennai India Velammal Institute of Technology Department of Mechanical Engineering Tamil Nadu Chennai601204 India Sr University Department of Electrical and Electronics Engineering Telangana Warangal1506371 India Kcg College of Technology Department of Civil Engineering Karapakkam Chennai600097 India

ISBN: (纸本)9798350344837

'The cloud' is shorthand for a cloud-based computer infrastructure that helps make other technologies possible. The workload is split among several cloud-based, virtual computers according to some factors. However, cloud computing (CC) provides options for dealing with issues like job scheduling, such as improved task scheduling. To begin, we present a Dynamic Weighted Round-Robin strategy for more efficient cloud-based task allocation. Because of its efficiency in optimizing schedules in light of finite resources, jobs' relative importance, and available time, the SPMOA approach comes highly recommended. Second, a heuristic method called Hybrid Particle Swarm Parallel Ant Colony Optimization is introduced to solve the problem of task execution latency in SPMOA-based task scheduling. In conclusion, we enhance cloud-based task scheduling by creating a fuzzy logic framework for MLOA. Both the inertial mass of the PSO and the pheromone trails left by the P ACO are modified using fuzzy methods. Fuzzy Hybrid Particle Swarm Parallel Ant Colony Optimization is the optimal method for scheduling tasks in the cloud. The strategy reduces downtime due to waiting and procedures while simultaneously increasing output and minimizing inefficiency. © 2024 IEEE.

关键词： Ant colony optimization

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Research on the Construction of Command and Control System for Multi Domain Parallel Operations 8

Research on the Construction of Command and Control System f...

引用

8th IEEE Information Technology and mechatronics engineering conference, ITOEC 2025

作者： Liu, Dayong Dong, Zhiming Li, Liang Qiu, Xuehuan Gao, Jiancheng Army Academy of Armored Forces Beijing100072 China 32302 Troops of PLA Shijiazhuang050003 China

ISBN: (纸本)9798331517915

In the era of intelligent warfare, multi domain space warfare consisting of physical domain, in-formation domain, and cognitive domain is the mainstream form. Based on a comprehensive analysis of the development trend of command and control systems, the connotation of the concept of multi domain parallel operations, and the capability requirements of command and control systems, an innovative concept of a command and control system for multi domain parallel operations was proposed. The system architecture, system composition, key technology groups, and deployment strategies of the system were designed, with a particular focus on analyzing technical difficulties and planning implementation paths, in order to provide useful references for the design and development of the new generation of command and control systems. © 2025 IEEE.

关键词： computer control systems

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Spatiotemporally Resolved Dual-band Hyperchromatic Structural Color with a Mesoporous Metamaterial

Spatiotemporally Resolved Dual-band Hyperchromatic Structura...

引用

CLEO: science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of conference on Lasers and Electro-Optics

作者： Kumar, Nithesh Dos Santos, Estevao Marques Talukdar, Tahmid H. Ryckman, Judson D. Holcombe Department of Electrical and Computer Engineering Clemson University SC29634 United States

We present an approach to achieve highly responsive structural color utilizing dual-band porous silicon rugate filter metamaterials combined with dichromatic laser illumination. Spatiotemporally resolved sensing exper... 详细信息

关键词： Mesopores

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Application of Machine Learning Models for Predicting Students' Performance in Mathematics: A K-Fold Approach

Application of Machine Learning Models for Predicting Studen...

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2024 International conference on science, engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Ale, Felix Ikpaya, Ikpaya D. Danyan, Ilesanmi Opateye, Goodness O. Onwodi, Gregory Agboola, Olufemi O. National Space Research & Development Agency Department of Engineering & Space Systems Abuja Nigeria National Space Research & Development Agency Ground Station & Mission Control Abuja Nigeria Achievers University Department of Mechanical & Mechatronics Engineering Owo Nigeria National Open University of Nigeria Department of Computer Science Abuja Nigeria

ISBN: (纸本)9798350358155

Mathematics plays a pivotal role in science, technology and engineering. It is one of the compulsory subjects to gain admission into a higher institution in Nigeria. Considering its importance, students' performance has been a significant concern for most educators, government, parents and guardians. This study aims to predict students' performance in mathematics using the K-fold approach to support effective decision-making and policy implementation on mathematics. The primary dataset was collected from 192 senior secondary schools, and one mathematics student was randomly selected from five Senior Secondary Schools in Bwari Area Council, Abuja, and used as a sample. Students' Mathematics Achievement Test (SMAT) was used as the instrument to collect data. The data was processed and modelled using the Python Programming language. Thus, five machine learning models were trained and evaluated to overcome overfitting using four-, five - -, and six-fold K-Fold cross-validation techniques. Five folds performed best for all the models except for the Support Vector Regressor, which performed best with six folds. The evaluation of the models showed that the Light Gradient Boosting Model outperformed others with a Mean Absolute Error of 12.642 and a Root Mean Square Error of 15.894. The models were significantly influenced by the students' personal study time, friends' assistance, and the parents' educational background. It is therefore recommended that academic researchers, educational authorities in Nigeria, and relevant stakeholders use and improve on this model to predict the students' scores and assist them in achieving great performance in mathematics. © 2024 IEEE.

关键词： Mean square error

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Site-Controlled Plasmon-Assisted Single Photon Emission in Locally Strained Few-Layer Hexagonal Boron Nitride

Site-Controlled Plasmon-Assisted Single Photon Emission in L...

引用

CLEO: Fundamental science, CLEO:FS 2024 - Part of conference on Lasers and Electro-Optics, CLEO 2024

作者： Sakib, Mashnoon Alam Triplett, Brandon Hussain, Naveed Senichev, Alexander Xu, Xiaohui Momenzadeh, Melika Boltasseva, Alexandra Shalaev, Vladimir M. Shcherbakov, Maxim R. Department of Electrical Engineering and Computer Science University of California IrvineCA92697 United States School of Electrical and Computer Engineering Birck Nanotechnology Center Purdue Quantum Science and Engineering Institute Purdue University West LafayetteIN47907 United States Oak RidgeTN37931 United States Department of Materials Science and Engineering University of California IrvineCA92697 United States Beckman Laser Institute and Medical Clinic University of California IrvineCA92612 United States

ISBN: (纸本)9781957171395

We report on the site-controlled Purcell-enhanced quantum emitters in hexagonal boron nitride by strain-induced activation in gold-coated silicon nanoposts. The room temperature emitters show a second-order autocorrelation function value at zero time delay g(2)(0) of down to 0.29, lifetimes shortened to 0.5 ns, and single photon emitter yield of 28%. © Optica Publishing Group 2024, © 2024 The Author(s)

关键词： Gold coatings

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A Proposed Technique for Management of Flow Rules in SDN using Blockchain

A Proposed Technique for Management of Flow Rules in SDN usi...

引用

2022 International conference on Electrical, computer, Communications and mechatronics engineering, ICECCME 2022

作者： Mukhejee, Abhijeet Chatterjee, Rajeev Mandal, Jyotsna Kumar National Institute of Technical Teachers' Training & Research Department of Computer Science & Engineering Kolkata India Department of Computer Science & Engineering University of Kalyani Kalyani Nadia India

ISBN: (数字)9781665470957

ISBN: (纸本)9781665470957

Software-Defined Networking (SDN) changes the concept of traditional computer networking. In SDN, the control mechanism is handled by separate plane known as control plane. Data communication is taken care by data plane. To manage the control plane, a dedicated computing resource known as SDN controller is deployed. The standalone SDN architecture does not have any backup and system and security system. In case of any failure, the entire networking details as well as flow rules are lost. The authors proposed a solution to address the problems using blockchain and Back-up and Restoration System (BRS). Flow rules are used to manage the devices in the infrastructure layer where rules are forwarded to forwarding plane, that manages individual devices. At the control layer the flow rules of the SDN are managed in the controller using blockchain. By decentralizing the management of flow rules, the entire system become robust and secure. In case of controller failure, the BRS provides failure recovery by assigning nearest controller to the failed controller. Hence the entire network performs uninterruptedly. © 2022 IEEE.

关键词： Controllers

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Reinforcing Feature Distributions of Hidden Units of Boltzmann Machine using Correlations

Reinforcing Feature Distributions of Hidden Units of Boltzma...

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2022 International conference on mechatronics engineering and Artificial Intelligence, MEAI 2022

作者： Cai, Peixu Shen, Wangze Yang, Ruohan Zhou, Qixian Department of Computer Science Boston University MA02215 United States College of Literature Science and the Arts University of Michigan MI48109 United States Alibaba Group Shanghai201199 China Arts and Science University of Toronto TorontoONM5S 1A1 Canada

ISBN: (纸本)9781510663169

This paper introduces and analyses the method of applying Neuroscience methods to Boltzmann Machine, involving a combination of cognitive psychology, information theory, and dynamical systems. We utilized the emergent property of the probability of hidden layers to find the pattern of how units are behaving when stimulated by the visual layer and research into enhancing the predictive encoding capability of the encoding layer. We measure the connections and links between the units of the encoding layer by approximating it with the probability distribution of two units' activation behaviours. For example, the portion of the Auditory cortex responsible for processing auditory information, such as music, differs from the sections responsible for processing visual information, although they can still be linked and active concurrently. Besides, Neurons can modify their connections by learning new information and reinforcing the connections that have been utilized more frequently, and forgetting the connections if the probability distributions of two units diverge much. The Boltzmann machine is the probabilistic inference machine for ground truth using the free energy principle. The latter has stepped further from the concept to interpret cortical responses as a fundamental of intelligent agency. With simple and random interactions of each neuron, this 'intelligent agency' could achieve sophisticated functions in a specific area of a brain. Randomness is also a vital aspect of learning since it may achieve balance and embrace regularities according to Ramsey's Theory. © 2023 SPIE.

关键词： Probability distributions

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Research on Complexity Evaluation Method for Dispatch Automatic Generation Control Software Based on GRA 8

Research on Complexity Evaluation Method for Dispatch Automa...

引用

8th IEEE Information Technology and mechatronics engineering conference, ITOEC 2025

作者： Wei, Zechen Wang, Nanyang Zhang, Zexi Chen, Juntao Li, Yujia Qi, Xiaolin China Electric Power Research Institute Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation Technology Beijing China

ISBN: (纸本)9798331517915

With the increasing complexity of dispatch automatic generation control (AGC) systems, evaluating the software complexity has become essential for optimizing performance and improving reliability. This paper investigates the complexity evaluation of AGC software by analyzing its operational and functional characteristics. A complexity evaluation model is constructed from the perspectives of code structure and software structure. The model introduces a structural complexity indicator based on functional network density and evaluates corresponding metrics using the grey relational analysis (GRA) comprehensive evaluation method. Case studies are conducted to verify the feasibility and applicability of the proposed method. The results demonstrate that this model and evaluation method can provide valuable support for improving software quality, optimizing software testing strategies, and guiding the development of more efficient AGC systems. © 2025 IEEE.

关键词： computer software selection and evaluation

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Wildfire Spread Prediction Using Attention Mechanisms in U-NET

Wildfire Spread Prediction Using Attention Mechanisms in U-N...

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2023 International conference on Electrical, computer, Communications and mechatronics engineering, ICECCME 2023

作者： Shah, Kamen Pantoja, Maria California Polytechnic State University Dept. Computer Science and Software Engineering San Luis Obispo United States

ISBN: (纸本)9798350322972

Global warming has increased large-scale natural disasters at an alarmingly greater frequency. These natural disasters affect humans and the ecosystems that all species rely upon for food and shelter. A significant byproduct of global warming is the emergence of mega-fires, which are wildfires that burn more than 100,000 acres. Mega fires have exhibited the capacity to destroy entire ecosystems and urban areas. Researchers forecast a significant increase in wildfires during the next decade. This is a fundamentally growing problem that mandates modern solutions. Currently, simulation models are employed to predict wildfire propagation and aid firefighters in suppressing them. However, these methods are computationally expensive and often inaccurate. A recent advance in this area is the usage of neural networks (NN), which are systematically more accurate and computationally efficient. This paper focuses on predicting wildfire spread using NN with an attention mechanism to improve spatial recognition and overall performance in neural networks for wildfire spread prediction. We train different models on 12 distinct observational variables derived from the Google Earth Engine catalog. Evaluation is conducted with accuracy, Dice coefficient score, ROC-AUC, and F1-score. Results show that when augmenting segmentation models with attention mechanisms, the attention component improves feature suppression and recognition, improving overall performance. Furthermore, we use ensemble modeling to reduce bias and variation, leading to more consistent and accurate predictions. The architecture presented in this research achieved a ROC-AUC score of 86.2% and an accuracy of 82.1% when inferencing on wildfire propagation at 30-minute intervals. © 2023 IEEE.

关键词： Forecasting

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Advanced Facial Expression Classification with CNN-Transformer Integration for Human-computer Interaction 9

Advanced Facial Expression Classification with CNN-Transform...

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9th International conference on computer science and engineering, UBMK 2024

作者： Azmoudeh, Ali Gumussoy, Cigdem Altin Ekenel, Hazim Kemal Istanbul Technical University Department of Computer Engineering Istanbul Turkey Istanbul Technical University Department of Industrial Engineering Istanbul Turkey

ISBN: (纸本)9798350365887

This paper presents an advanced approach to Facial Expression Classification (FEC) to evaluate user behavior in online shopping environments. In this application, users' videos are captured as they accomplish tasks under varying circumstances, including scenarios with and without moderator aid. We utilized and trained a simplified POSTERv1 model on the AffectNet dataset to analyze the captured videos. The model processes frames and performs first, face detection b y using the MTCNN approach. Then, the detected face is resized and normalized to ensure compatibility with the input requirement of the deep learning architecture. The normalized face image is fed to the facial landmark detector and facial feature extractor networks. The outputs from these two parallel pipelines are provided to the cross-fusion transformer encoder to capture multi-scale features and enhance expression recognition accuracy. Experimental results demonstrate the model's efficacy, achieving notable accuracy across AffectNet, CK+, and FER2013 datasets. Our approach effectively addresses real-world challenges in FEC by creating a custom dataset and comparing emotional responses in moderated versus non-moderated scenarios, highlighting its potential for Human-computer Interaction applications. © 2024 IEEE.

关键词： Convolutional neural networks

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